Module manager: Dr Natasha Shakhlevich
Email: N.Shakhlevich@leeds.ac.uk
Taught: Semester 1 (Sep to Jan) View Timetable
Year running 2024/25
| COMP1511 | Introduction to Discrete Mathematics |
| COMP1721 | Object Oriented Programming |
This module is not approved as a discovery module
Algorithms are the underlying concept of which computer programs are the embodiment of. In order to appreciate a good solution to a problem it is essential that 'good' can be quantified in some rigorous manner. The primary focus of this module is to develop a toolkit of knowledge and skills used in the design and analysis of algorithms and data structures. This module builds on previous mathematics modules and relies on the skills developed there for justifying the correctness of algorithms and their time and space requirements.
This module introduces the basics of algorithm design and analysis and provides students with the opportunity to practice these new skills on classical computer science algorithms and data structures. This module develops abstract problem-solving skills and contributes to developing computer science professional who are capable of tackling real world problems.
On successful completion of this module a student will have demonstrated the ability to:
- analyse an algorithm in terms of time complexity.
- justify the correctness of an algorithm.
- trace an algorithm communicated in pseudo code.
- develop algorithms for real world problems.
- select an appropriate data structure for a given problem.
- articulate key concepts from the topic in a clear and rigorous manner.
Syllabus This module covers the following 4 topic areas:
-Algorithm design: iterative algorithms, recursive algorithms, brute force algorithms and divide-and-conquer.
-Algorithm analysis: time and space complexity, worst case analysis and big-O notation.
-Searching & sorting : sequential and binary search, selection sort, insertion sort, quicksort, merge-sort and heapsort.
-Data structures: arrays, lists, stacks, queues and heaps.
| Delivery type | Number | Length hours | Student hours |
|---|---|---|---|
| Lecture | 20 | 1 | 20 |
| Tutorial | 10 | 1 | 10 |
| Private study hours | 70 | ||
| Total Contact hours | 30 | ||
| Total hours (100hr per 10 credits) | 100 | ||
Taught session preparation: 9 hours
Taught session follow-up: 9 hours
Self-directed study: 19 hours
Assessment activities: 24 hours
Coursework and labs.
| Assessment type | Notes | % of formal assessment |
|---|---|---|
| In-course Assessment | Coursework 1 | 10 |
| In-course Assessment | Coursework 2 | 10 |
| Total percentage (Assessment Coursework) | 20 | |
Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated
| Exam type | Exam duration | % of formal assessment |
|---|---|---|
| Standard exam (closed essays, MCQs etc) (S1) | 2.0 Hrs 0 Mins | 80 |
| Total percentage (Assessment Exams) | 80 | |
This module will be reassessed by examination only.
The reading list is available from the Library website
Last updated: 9/25/2024
Errors, omissions, failed links etc should be notified to the Catalogue Team